Training in realistic situations often yields substantial performance improvement. However, such realistic training can pose a high risk to participants, especially if the training involves potentially dangerous tasks or operations in hostile and/or potentially threatening environments. So, to provide participants with reduced risk environments for training, the realistic situations can be simulated using motion capture, where the term ‘motion capture,’ refers generally to capturing any appropriate motion of an object (animate or inanimate) in the real-world using appropriate sensors and translating the motion in the real-world to a motion of a computer-generated model (herein interchangeably referred to as ‘avatar’) of the object in a virtual environment.
In the motion capture simulation, the real-world environment may include a physical volume that has a level or flat surface while the virtual environment may include real-world elevation characteristics that includes but not limited to, undulating terrain, natural or man-made inclines, steps, roof-tops, ditches, spans, and so on. Conventional technology provides a one to one translation of participants in the real-world to their corresponding avatar in the virtual environment which may not take into consideration the real-world elevation characteristics in the virtual environment. Accordingly, an ability to navigate a virtual environment that has real-world elevation characteristics while participants move in a flat or level surface in the real-world may be restrained. For example, if the avatar of the participant has to walk over a hill in the virtual world, a one on one translation of the motion of the participant in the real-world along a level and flat surface may result in abnormalities such as the legs of the corresponding avatar being buried under the hill or floating above the hill. Such abnormalities may increase a suspension of disbelief barrier that may cause a realism of the simulation to be compromised. Further, such abnormalities may reduce a training effectiveness of the participant and the participant may become frustrated.
Conventional technology addresses the above mentioned limitations by providing props in the real-world that resemble the real-world elevation characteristics in the virtual environment. In other words, solutions offered by conventional technology would require a real-world volume to be designed to have features that resemble the elevation characteristics of the virtual environment. For example, if there is a car in the virtual environment, the physical volume in which the participants are located should be designed to include a platform that resembles a car. Such designing of physical volumes have features (e.g., props, platforms, etc.) that resemble one or more of the elevation characteristics in the virtual environment characteristics would be cost prohibitive and time consuming. Other solutions to address the above-mentioned limitations include simplifying the design of the virtual environment to consist of only level or flat surfaces. In other words, the virtual environment is simplified to remove all surface variations or spatial elevation characteristics. Such redesigning of the virtual environment severely restricts the type of virtual environment environments available for the participants to train. In view of the foregoing discussion of representative shortcomings, need for improved mapping from the real-world to the virtual environment having real-world elevation characteristics that addresses the above-mentioned shortcomings is apparent.